pandas split by space
# importing pandas module
import pandas as pd
# new data frame with split value columns
data["Team"]= data["Team"].str.split(" ", n = 1, expand = True)
# df display
datapandas split by space
# importing pandas module
import pandas as pd
# new data frame with split value columns
data["Team"]= data["Team"].str.split(" ", n = 1, expand = True)
# df display
datahow to use split in pandas
import pandas as pd
# new data frame with split value columns
data["Team"]= data["Team"].str.split(" ", n = 1, expand = True)
# df display
datasplit a pd dataframe
In [255]: df = pd.DataFrame(np.random.rand(5, 6), columns=list('abcdef'))
In [256]: df
Out[256]:
a b c d e f
0 0.823638 0.767999 0.460358 0.034578 0.592420 0.776803
1 0.344320 0.754412 0.274944 0.545039 0.031752 0.784564
2 0.238826 0.610893 0.861127 0.189441 0.294646 0.557034
3 0.478562 0.571750 0.116209 0.534039 0.869545 0.855520
4 0.130601 0.678583 0.157052 0.899672 0.093976 0.268974
In [257]: dfs = np.split(df, [4], axis=1)
In [258]: dfs[0]
Out[258]:
a b c d
0 0.823638 0.767999 0.460358 0.034578
1 0.344320 0.754412 0.274944 0.545039
2 0.238826 0.610893 0.861127 0.189441
3 0.478562 0.571750 0.116209 0.534039
4 0.130601 0.678583 0.157052 0.899672
In [259]: dfs[1]
Out[259]:
e f
0 0.592420 0.776803
1 0.031752 0.784564
2 0.294646 0.557034
3 0.869545 0.855520
4 0.093976 0.268974splitting column values in pandas
df[['A', 'B']] = df['AB'].str.split('@', 1, expand=True)
#'@' - Split at @
#1 = Axis 1 i.e on column levelCopyright © 2021 Codeinu
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